An improved algorithm using instantaneous frequency estimation successfully extracts respiration signals from ECGs measured by conductive textile electrodes with high correlation to standard chest-belt sensors.
May enable respiration monitoring from textile ECGs without chest belts; leaves open clinical validation.
In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) in home healthcare is proposed. The whole system consists of two-lead electrocardiogram acquisition using conductive textile electrodes located in bed, baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problems of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we are proposing a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 male subjects, and we obtained satisfactory respiration signals that showed high correlation (r(2) > 0.8) with the signal acquired from the chest-belt respiration sensor.
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Park et al. (2008) studied this question.
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